Two new spectral algorithms, GDSE and GDE, learn Euclidean embeddings of hypergraphs by optimizing a smoothed reconstruction loss, recovering planted geometry and improving spurious/missing membership detection and clustering.
Class of models for random hypergraphs
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Optimization of geometric hypergraph embedding
Two new spectral algorithms, GDSE and GDE, learn Euclidean embeddings of hypergraphs by optimizing a smoothed reconstruction loss, recovering planted geometry and improving spurious/missing membership detection and clustering.